ALOS-2 Project Manager Shin-ichi Sobue
JAXA Earth Observation Satellites Targets (JFY) 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 [Land and disaster monitoring] Disasters & Resources Climate Change & Water Cycle Water Cycle Climate Change GHGs TRMM / PR [2012 ] ALOS-2 / PALSAR-2 [1997 2015] [Precipitation 3D structure] GPM / DPR [Wind, SST, water vapor, precipitation,] GCOM-W / AMSR2 [2009 ] GOSAT /FTS, CAI [CO 2, Methane] [Vegetation, aerosol, cloud, SST, ocean color] GCOM-C / SGLI EarthCARE / CPR [CO 2, Methane, CO] Advanced SAR Advanced Optical Research the hosted payload capability of AMSR s successor sensor with the GOSAT-3 [Cloud and aerosol 3D structure] GOSAT-2 GOSAT-3 Mission status: On orbit Development Study 1
JAXA s EO scenario Geospatial Information By Satellite Remote Sensing JAXA s Earth Observation Programs 1. Disaster Risk Management Crustal Deformation Monitoring Flood Early Warning Landslide Monitoring 2. Climate Change (Mitigation/Adaptation) Mitigation GHG Monitoring Mitigation Forest Monitoring Adaptation Prediction of extreme weather event 3. New Applications Ocean DSM Infrastructure Monitoring 2
Advanced Land Observing Satellite-2 (ALOS-2) Mission objectives - Disaster monitoring (Earthquake, Volcano, Landslide, Flooding, ) - Environmental monitoring (Forest, Ice sheet, ) - Agriculture, natural resources, and ocean - Technology development Mission sensor PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar 2) Launch May 24, 2014 H-IIA launch vehicle Mass Lifetime 2.1 tons 5 years (target: 7 years) Y Z X Orbit Sun-synchronous, 628 km altitude, 14 days revisit, Orbit control: +/- 500 m Local sun time 12:00±15 min (descending) Solar Arrays PALSAR-2 (Phased Array type L-band Synthetic Aperture Radar 2) Mission data transmission 24:00±15 min (ascending) X-band: 800 Mbps (16 QAM), 200/400 Mbps (QPSK) PALSAR-2 antenna X-band downlink antenna 3
Daichi-2 (ALOS-2) Mission Objectives: Earthquake Disaster monitoring Volcano Flooding Ocean Environment and land management Forest and wetland Ice Agriculture & natural resources 4
Global Precipitation Measurement (GPM) KaPR: 35.5GHz radar (phased array) GPM Core Observatory GMI (Microwave Imager) KuPR: 13.6GHz radar (phased array) Constellation Satellites by international partners GPM is an international mission consisting of the GPM Core Observatory and Constellation Satellites for high accurate and frequent global precipitation observation. Core Observatory: developed under NASA and JAXA equal partnership. Constellation satellites: provided by international partners (includes GCOM-W1). Dual-frequency Precipitation Radar (DPR) developed by JAXA and NICT DPR is composed of two radars: KuPR & KaPR GPM Core Observatory was successfully launched on 28 Feb. 2014 (JST). Core Observatory by NASA-JAXA 5
6 JAXA s Contribution to Forecasting GSMaP_NOW over Himawari-8 area start just now! Global Satellite Mapping of Precipitation (GSMaP) Global Rainfall Watch (GSMaP_NRT/MVK) Realtime Rainfall Watch (GSMaP_NOW) Champi Olaf Patricia GSMaP (Global) observed Hurricane Patricia and Olaf, and Typhoon Champi: 20-24 Oct. 2015, hourly animation Rapidly changing precipitation phenomena need frequent observations. Global rainfall map merging GPM Core Observatory, polar orbiting microwave radiometer/sounders, and geostationary infrared radiometers. JAXA Global Rainfall Watch (4-hr delay) : http://sharaku.eorc.jaxa.jp/gsmap JAXA Realtime Rainfall Watch (Himawari-area): http://sharaku.eorc.jaxa.jp/gsmap_now
Typhoon 19 by GSMaP
Typhoon 19 by HDTV camera on JEM/ISS
Inundation area estimation by Sentinel-Asia using ALOS-2 http://arcg.is/2h8rs7f
Inundated Area Detection Using RADAR Data 10
Disaster Risk Management Flood Early Warning Water Management: Reduce Flood Damage Satellite data and in-situ data are merged to predict flood of lower river region several days before. Based on this information, the warning and evacuation call are sent directly to residents. Global Satellite Mapping of Precipitation (GSMaP) In-situ Data GPM Model Partners Warning Message Global satellite data is effective to grasp the situation on water rising of International crossborder rivers. In Bangladesh, flood forecasting made it possible to take measures for crops in advance of damages. The farmers have a few days for harvest until flood at upper river flows down to lower areas and causes damage to the crops. (System will be organized) 11
GSMaP based Landslide Warning System (GLWS) - Pilot Study in the Philippines - GSMaP rainfall archives are analyzed by a machine learning method (RBFN), and critical lines (CLs) of hourly rainfall and soil moisture index (SMI) are selected. The system monitors rainfall in real-time and determines the landslide warning level. Rainfall monitoring Sensor network Automatic prediction System AWS Model preparation GSMaP-Now Satellite Hazard maps, Criteria Application Analysis / warning Agency/ Local gov. Maps Warning criteria
Overview of the prototype-system The Landslide and Flood disaster Early Warning System with GSMaP Input GSMaP AWS GSMaP Correction Corrected GSMaP Tank model Soil Moisture Index Run-off 10km First user list is necessary (User s Name and Email address) Login: User ID Password Landslide warning system by Non-leaner Critical Line Flood warning system by estimating water level Web Browser Alert of landslide disaster Output Alert of flood disaster
GFAS-II(Global Flood Alert System ver.2) GFAS developed by IDI is a system to apply global satellite precipitation estimates to flood forecasting. GFAS utilizes GSMaP as a means of estimation to provide global flood risk map that is display on the Internet. GFAS-II, upgraded in 2017, is PC & Smartphone-friendly version, and available to everyone around the world. GFAS-II currently has the displays for 5 languages (English, Japanese, Spanish, German and Vietnamese). Animation display of rain area Captured Image of GFAS-II web site 72 Cumulative precipitation of 11:00, May 23-26, 2015 < 5yr precip. 10yr precip. 30yr precip. > 30yr precip. Display / Hide of the menu Legend Search Location by place name - Jump to the Current Location - Zooming Selection of Information NRT or NOW - Prob :Probable Rainfall (Risk map) - Rain :GSMaP (Observed Rainfall) Other Functions -Selection of language EN, ES, DE, VN -Selection of layer Map, Aerial Photo Selection Cumulative rainfall 1h, 3h, 12h, 24h, 72h [Smart Phone] [PC] http://gfas.internationalfloodnetwork.org/n-gfas-web/sp/frmmain.aspx http://gfas.internationalfloodnetwork.org/n-gfas-web/pc/frmmain.aspx 14
ADB Joint Project on Drought Monitoring Target: Greater Mekong Subregion (GMS) - Add free satellite-based drought information to GMS-AIN GMS-AIN (Great Mekong Subregion Agricultural Information Network) Free data and automatically updated -> No operational cost Drought Indices and alerts -KBDI (Keetch-Byram Drought Index); daily, 10km 15 15 15
Example: Rice Growth Outlook in Vietnam Rice Growth Outlook (September 2016) Precipitation anomaly in first half of September Precipitation (Hanoi Province) Vietnam In the North, the seeding of autumn-winter rice (wet season rice) is completed. The sown area is around 1.1 million ha, accounting for 99.2% of the last year area. The weather in the North is not good for paddy due to storm and flood. In the South, the summer-autumn rice enters a harvesting time. The harvested area is around 1.0 million ha.. Satellite derived agro-met information can support to judge rice growth.
Vietnam Data Cube - SAR based rice crop monitoring scheme JAXA ALOS-2 GA/CSIRO Ground data VNSC GEORIICE ScanSAR every 42 days ESA Data Cube Statistical info MARD Sentinel Met info MONRE Dual every 12 days MODIS Landsat Analyzed info CSIRO VNSC, VAST, MARD
Rice Crop Mapping in Southeast Asia ADB Technical Assistance project and SAFE project under the APRSAF have successfully demonstrated INAHOR using ALOS-2 with the mapping accuracy of 80-90% for the target provinces. Scaling-up for major rice producing areas is currently demonstrated in Vietnam and Indonesia. ADB TA Project Laos Thailand Vietnam (North) Philippines [2014-2016] Rice-planted Area Mapping Software (INAHOR) SAFE Project (Test site) Myanmar Cambodia SAFE Project (Scaling-up) [2016-] Vietnam (Mekong Delta) Indonesia [2014-] 18
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ALOS-2 ScanSAR data provision For GEOGLAM and CEOS Under GEOGLAM/Asia Rice and ALOS K&C project, JAXA provides ScanSAR data at technical demonstration sites (100km x 100km one province) in Cambodia, Myanmar, Malaysia, Lao, India, China, Thailand and Taiwan to Asia Rice crop team members with ALOS-2 download system now. Under Asia Pacific regionsal space agency forum (APRSAF) framework with GEOGLAM/Asia Rice, JAXA provides scale up activity for Indonesia (Top 10 rice crop production provinces) and Vietnam (Mekong) Proposal from JAXA Under cooperation with JICA and commerical data providers, JAXA starts to prepare to provide on-line access to intermidate JJ-FAST products = ScanSar ortho-slop corrected DN data and/or ALOS-2 25m path ortho-slop correct data (gamma naught) from ALOS- 2 path mosaic to selected countries for each target country data where JAXA, ADB and APRSAF countries have cooperative aggeement (Indonesia, LaoPDR, Thailand, Philippine, Low Mekong (Vietnam + Cambodia)) for governmental use in respecting countries. JAXA starts to prepare sample data of ScanSAR data to ingest Vietnam data cube and propose CEOS ARD of SAR (1-5 degree mesh tiled data or path orth-slop corrected data) in cooperation with CEOS SEO (NASA) Other than ASEAN area, JAXA will discuss with commercial data distributor to have same framework of ALOS-2 ScanSAR intermidate product to target countrys governmetal use if CEOS and GEO community are interested in.
Coordination status with respecting countries 1. Vietnam VNSC and CSIRO/GA already prepare to implement CEOS Mekong data cube by the end of this year VNSC and JAXA agreed to coordinate ALOS-2 ScanSAR data ingestion with rice crop area estimation software (INAHOR) to CEOS Mekong data cube JAXA and VNSC will finalize MOU for Vietnam data cube with ALOS-2 ScanSAR data and will have Data cube workshop as a pre-workshop of GEOSS-AP agriculture working group (WG5) 2. Indonesia LAPAN, MOA and JAXA agreed to coordinate coordinate ALOS-2 ScanSAR data ingestion to LAPAN data archive JAXA and LAPAN start to coordinate MOU to archive and use ALOS-2 ScanSAR data in Indonesia 3. Thailand JAXA and GISTDA start to discuss ALOS-2 ScanSAR data of Thailand and Lao provision to GISTDA
JAXA s EO Data Portals Portal Name and URL G-Portal (GPM, TRMM, JERS-1, AQUA/AMSR-E...etc.) https://www.gportal.jaxa.jp/gp/top.html *Free andn Open Data GCOM-W: Global Change Observation Mission-Water http://suzaku.eorc.jaxa.jp/gcom_w/data/data_w_index.html *Free and Open Data GSMaP: Global Satellite Mapping of Precipitation http://sharaku.eorc.jaxa.jp/gsmap_crest/index.html *Free and Open Data Precise Global Digital 3D Map "ALOS World 3D" Homepage (30m resolution) http://www.eorc.jaxa.jp/alos/en/aw3d/index_e.htm *Free and Open Data High resolution data is available through commercial distributors. ALOS-2: PASCO (http://en.alos-pasco.com/) ALOS World 3D (5m resolution): NTT DATA and RESTEC (http://aw3d.jp/en/index.html)
Future Missions 23
GCOM-C: Global Change Observation Mission- Climate shortwave & thermal InfraRed (T) Scanner (IRS) Polarization (along-track slant) radiometer (P) Visible & Near infrared pushbroom Radiometer (VNR) GCOM-C SGLI characteristics Orbit Sun-synchronous (descending local time: 10:30), Altitude: 798km, Inclination: 98.6deg Launch Date JFY 2017 Mission Life 5 years Scan Push-broom electric scan (VNR: VN & P) Wisk-broom mechanical scan (IRS: SW & T) Scan width 1150km cross track (VNR: VN & P) 1400km cross track (IRS: SW & T) Spatial resolution 250m (land and coastal areas), 500m, 1km Polarization 3 polarization angles for POL Along track tilt Nadir for VN, SW and TIR, & +/-45 deg for P 24 24
GOSAT-2 on orbit in early 2018 Upgrade in GOSAT-2 mission GOSAT achievement GOSAT target Measurement precision 0.5 ppm for CO 2 5 ppb for CH 4 2ppm for CO 2 12ppb for CH 4 4 ppm for CO 2 32 ppb for CH 4 Flux estimation 1000km for land 2000km in sub-continental scale Anthropogenic emission Ecosystem carbon exchange Aerosol 25 monitoring CO to distinguish emission source Chlorophyll fluorescence to place constrains on GPP Aerosol size distribution and its property 25
Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) 26 To reduce the uncertainties in global warming prediction by measuring the three dimensional structure of clouds and aerosols, which are most uncertain parameter in the numerical climate models. Characteristics Life Orbit Mass/Power Launch Instruments 3 years Sun-Synchronous (around 400km) About 2.2 t/ about 3.4 kw FY 2019 (TBC) CPR: Cloud Profiling Radar (JAXA/NICT) ATLID: Atmospheric Lidar (ESA) MSI: Multi-Spectral Imager (ESA) BBR: Broadband Radiometer (ESA) Satellite bus: Airbus DS Satellite launch: ESA CPR (Cloud Profile Radar)
ALOS successors: Advanced Optical Satellite and Radar Satellite Advanced Optical Satellite (ALOS-3) Hazard Map Advanced Radar Satellite (ALOS-4) Characteristics Life Orbit Mass 7 years Sun-Synchronous (670km) About 2.7 t Launch FY 2020 Resolutio n Panchromatic : 0.8m (swath: 70km) Multi: 3.2m (swath: 70km) High Precision 1/25,000 Map (C) GSI Crucial Deformation 地 chikaku 地殻変動殻変動 Magma Chamber マグマの上昇 Rising Magma Estimate situation of magma chamber under the ground and faulting Take a decision for evacuation Characteristics Life Orbit Mass 7 years Sun-Synchronous (628km) About 3 t Launch FY 2020 Resolution Spotlight 1 3 m (swath: 35km) Strip map 3/6/10m (swath: 200km) ScanSAR 25m (swath: 700km) 27
Thank you very much for your attention. sobue.shinichi@jaxa.jp @Tsuruoka, Yamagata Pref. TDS Site in Japan 28